abstractive_model.py

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("EE21/Fine-tuned-BART-ToS-Summarization")
model = AutoModelForSeq2SeqLM.from_pretrained("EE21/Fine-tuned-BART-ToS-Summarization")

def summarize_with_bart(input_text):
    inputs = tokenizer.encode("summarize: " + input_text, return_tensors="pt", max_length=1024, truncation=True)
    summary_ids = model.generate(inputs, max_length=150, min_length=40, length_penalty=2.0, num_beams=4, early_stopping=True)
    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
    return summary